Evidence-Backed Templates and Security Playbooks for AI Coding Agents

Choose AGENTS.md, CLAUDE.md, Copilot instructions, or Cursor rules Start with the current support matrix, then maintain one shared policy with small tool-specific adapters.

Fix an MCP server that is connected but shows no tools Use the interactive fault tree and minimal tools/list reproduction before changing permissions.

Build an AGENTS.md template for Codex Generate a Node.js, Python, or monorepo starter with setup, verification, boundaries, and proof-of-done rules.

Check whether GitHub Copilot reads CLAUDE.md Use the surface-specific answer for IDE Chat, cloud agent, code review, and Copilot CLI.

Audit MCP authentication, permissions, and revocation Apply the source-backed security controls before an agent receives credentials or write access.

Review Cursor Enterprise security and Privacy Mode Verify current retention caveats, group policy, model controls, MCP access, and contract evidence.

Audit an instruction file in the browser Check setup, tests, scope, safety, and path compatibility without uploading repository content.

Replacing or complementing Claude Code? Compare seven Claude Code alternatives by workflow and keep staying with Claude Code as a valid result when no candidate improves the measured constraint.

Standardizing repository guidance? Compare instruction files by tool and surface before choosing the adapters your team will maintain.

Connecting agents to external tools? Review the MCP security checklist before granting credentials, network access, or write permissions.

Moving from one-shot prompts to repeatable workflows? Design loop engineering for AI coding agents with stop rules, verification commands, and cost limits before scaling Automations or /loop schedules.